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1 May 2013 Prediction of soil nutrient regime based on a model of DEM-generated clay content for the province of Nova Scotia, Canada
Zhengyong Zhao, M. Irfan Ashraf, Kevin S. Keys, Fan-Rui Meng
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Abstract

Zhao, Z., Ashraf, M. I., Keys, K. S. and Meng, F-R. 2013. Prediction of soil nutrient regime based on a model of DEM-generated clay content for the province of Nova Scotia, Canada. Can. J. Soil Sci. 93: 193-203. Soil nutrient regime (SNR) maps are widely required by ecological studies as well as forest growth and yield assessment. Traditionally, SNR is assessed in the field using vegetation indicators, topography and soil properties. However, field assessments are expensive, time consuming and not suitable for producing high-resolution SNR maps over a large area. The objective of this research was to develop a new model for producing high-resolution SNR maps over a large area (in this case, the province of Nova Scotia). The model used 10-m resolution clay content maps generated from digital elevation model data to capture local SNR variability (associated with topography) along with coarse-resolution soil maps to capture regional SNR variability (associated with differences in landform/parent material types). Field data from 1385 forest plots were used to calibrate the model and another 125 independent plots were used for model validation. Results showed field-identified SNRs were positively correlated with predicted clay content, with some variability associated with different landform/parent material types. Accuracy assessment showed that 63.7% of model-predicted SNRs were the same as field assessment, with 96.5% within ±1 class compared with field-identified SNRs. The predicted high-resolution SNR map was also able to capture the influence of topography on SNR which was not possible when predicting SNR from coarse-resolution soil maps alone.

Zhengyong Zhao, M. Irfan Ashraf, Kevin S. Keys, and Fan-Rui Meng "Prediction of soil nutrient regime based on a model of DEM-generated clay content for the province of Nova Scotia, Canada," Canadian Journal of Soil Science 93(2), 193-203, (1 May 2013). https://doi.org/10.1139/CJSS2012-016
Received: 21 February 2012; Accepted: 1 November 2012; Published: 1 May 2013
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